Sparse Blind Carrier-Frequency Offset Estimation for OFDMA Uplink

Carrier-frequency offset (CFO) estimation for uplink orthogonal frequency-division multiplexing access (OFDMA) systems is very challenging as it requires the estimation of multiple CFOs. In this paper, we propose a new framework referred to as sparse blind CFO estimation for interleaved uplink OFDMA. The proposed framework first discretizes the potential frequency offset ranges into discrete grid points, and formulates the original CFO estimation into a sparse signal recovery problem. Then, a novel two-stage matrix Bayesian compressive sensing-based CFO estimation method is proposed to solve the formulated problem. In the first stage, we employ a relatively large grid interval, and iteratively reconstruct a hyperparameter vector to generate a coarse estimation of multiple CFOs. The second stage reduces the grid interval, and the refined CFOs are estimated one by one through a novel low-complexity one-dimension searching algorithm. Numerical results show that the proposed method significantly outperforms conventional ones in terms of estimation accuracy, especially in the scenarios, such as low signal-to-noise ratios, large CFOs, and a large number of users.

I. Introduction

Orthogonal frequency-division multiplexing access (OFDMA) [1], [2] has been widely adopted in wireless broadband communication systems thanks to its robustness against frequency-selective fading. Theoretically, the orthogonality among OFDMA subcarriers avoids intercarrier interference (ICI) and multiple-access inter-ference (MAI), and features high efficiency in multiuser multiplexing [3]. In practical systems however, the mismatch in the transceiver oscillators and/or the Doppler effect due to the relative motion between transmitter and receiver produces carrier frequency offset (CFO) [4]. This results in the loss of subcarriers orthogonality, and introduces both ICI and MAI, significantly degrading the performance of OFDMA [5]. In downlink OFDMA transmission, CFO estimation is relatively simple since each user only needs to estimate a single CFO [6], [7]. In uplink OFDMA transmission, however, this issue becomes particularly challenging, as it requires the estimation of multiple CFOs from superimposed multiuser signals at the base station, and the optimal multidimensional exhaustive search method applied here is extremely complicated [5].